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<div class="title">from_meshes.h</div>  </div>
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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="preprocessor">#ifndef PCL_FEATURES_FROM_MESHES_H_</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="preprocessor">#define PCL_FEATURES_FROM_MESHES_H_</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160; </div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="preprocessor">#include &lt;pcl/features/normal_3d.h&gt;</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160; </div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="keyword">namespace </span>pcl</div>
<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;{</div>
<div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;  <span class="keyword">namespace </span>features</div>
<div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;  {</div>
<div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160; </div>
<div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;    <span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>NT&gt; <span class="keyword">inline</span> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;    computeApproximateNormals(<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;PointT&gt;</a>&amp; cloud, <span class="keyword">const</span> std::vector&lt;pcl::Vertices&gt;&amp; polygons, <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;PointNT&gt;</a>&amp; normals)</div>
<div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;    {</div>
<div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;      <span class="keywordtype">int</span> nr_points = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(cloud.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>.size());</div>
<div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;      <span class="keywordtype">int</span> nr_polygons = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(polygons.size());</div>
<div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160; </div>
<div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;      normals.<a class="code" href="classpcl_1_1_point_cloud.html#a82e0be055a617e5e74102ed62712b352">header</a> = cloud.<a class="code" href="classpcl_1_1_point_cloud.html#a82e0be055a617e5e74102ed62712b352">header</a>;</div>
<div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;      normals.<a class="code" href="classpcl_1_1_point_cloud.html#a2185a6453f8ad905d7bdf7b45754a160">width</a> = cloud.<a class="code" href="classpcl_1_1_point_cloud.html#a2185a6453f8ad905d7bdf7b45754a160">width</a>;</div>
<div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;      normals.<a class="code" href="classpcl_1_1_point_cloud.html#a4f34b45220c57f96607513ffad0d9582">height</a> = cloud.<a class="code" href="classpcl_1_1_point_cloud.html#a4f34b45220c57f96607513ffad0d9582">height</a>;</div>
<div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;      normals.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>.resize(nr_points);</div>
<div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160; </div>
<div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;      <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i = 0; i &lt; nr_points; ++i )</div>
<div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;        normals.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[i].getNormalVector3fMap() = Eigen::Vector3f::Zero();</div>
<div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160; </div>
<div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;      <span class="comment">// NOTE: for efficiency the weight is computed implicitly by using the</span></div>
<div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;      <span class="comment">// cross product, this causes inaccurate normals for meshes containing</span></div>
<div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;      <span class="comment">// non-triangle polygons (quads or other types)</span></div>
<div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;      <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i = 0; i &lt; nr_polygons; ++i )</div>
<div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;      {</div>
<div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">int</span> nr_points_polygon = (int)polygons[i].vertices.size();</div>
<div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;        <span class="keywordflow">if</span> (nr_points_polygon &lt; 3) <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160; </div>
<div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;        <span class="comment">// compute normal for triangle</span></div>
<div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;        Eigen::Vector3f vec_a_b = cloud.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[polygons[i].vertices[0]].getVector3fMap() - cloud.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[polygons[i].vertices[1]].getVector3fMap();</div>
<div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;        Eigen::Vector3f vec_a_c = cloud.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[polygons[i].vertices[0]].getVector3fMap() - cloud.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[polygons[i].vertices[2]].getVector3fMap();</div>
<div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;        Eigen::Vector3f normal = vec_a_b.cross(vec_a_c);</div>
<div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;        pcl::flipNormalTowardsViewpoint(cloud.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[polygons[i].vertices[0]], 0.0f, 0.0f, 0.0f, normal(0), normal(1), normal(2));</div>
<div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160; </div>
<div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;        <span class="comment">// add normal to all points in polygon</span></div>
<div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;        <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> j = 0; j &lt; nr_points_polygon; ++j )</div>
<div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;          normals.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[polygons[i].vertices[j]].getNormalVector3fMap() += normal;</div>
<div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;      }</div>
<div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160; </div>
<div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;      <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i = 0; i &lt; nr_points; ++i )</div>
<div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;      {</div>
<div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;        normals.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[i].getNormalVector3fMap().normalize();</div>
<div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;        pcl::flipNormalTowardsViewpoint(cloud.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[i], 0.0f, 0.0f, 0.0f, normals.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[i].normal_x, normals.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[i].normal_y, normals.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[i].normal_z);</div>
<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;      }</div>
<div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;    }</div>
<div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160; </div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160; </div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;    <span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>NT&gt; <span class="keyword">inline</span> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;    computeApproximateCovariances(<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;PointT&gt;</a>&amp; cloud, </div>
<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;                                  <span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;PointNT&gt;</a>&amp; normals,</div>
<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;                                  std::vector&lt;Eigen::Matrix3d, Eigen::aligned_allocator&lt;Eigen::Matrix3d&gt; &gt;&amp; covariances,</div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;                                  <span class="keywordtype">double</span> epsilon = 0.001)</div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;    {</div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;      assert(cloud.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>.size() == normals.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>.size());</div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160; </div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;      <span class="keywordtype">int</span> nr_points = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(cloud.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>.size());</div>
<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;      covariances.resize(nr_points);</div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; nr_points; ++i)</div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;      {</div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;        Eigen::Vector3d normal(normals.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[i].normal_x, </div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;                               normals.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[i].normal_y, </div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;                               normals.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[i].normal_z);</div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160; </div>
<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;        <span class="comment">// compute rotation matrix</span></div>
<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;        Eigen::Matrix3d rot;</div>
<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;        Eigen::Vector3d y;</div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;        y &lt;&lt; 0, 1, 0;</div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;        rot.row(2) = normal;</div>
<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;        y = y - normal(1) * normal;</div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;        y.normalize();</div>
<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;        rot.row(1) = y;</div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;        rot.row(0) = normal.cross(rot.row(1));</div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;        </div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;        <span class="comment">// comnpute approximate covariance</span></div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;        Eigen::Matrix3d cov;</div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;        cov &lt;&lt; 1, 0, 0,</div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;               0, 1, 0,</div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;               0, 0, epsilon;</div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;        covariances[i] = rot.transpose()*cov*rot;</div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;      }</div>
<div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;    }</div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160; </div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;  }</div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;}</div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160; </div>
<div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160; </div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;<span class="preprocessor">#endif </span><span class="comment">// PCL_FEATURES_FROM_MESHES_H_</span></div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160; </div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160; </div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html"><div class="ttname"><a href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a></div><div class="ttdoc">PointCloud represents the base class in PCL for storing collections of 3D points.</div><div class="ttdef"><b>Definition:</b> point_cloud.h:173</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html_a2185a6453f8ad905d7bdf7b45754a160"><div class="ttname"><a href="classpcl_1_1_point_cloud.html#a2185a6453f8ad905d7bdf7b45754a160">pcl::PointCloud::width</a></div><div class="ttdeci">uint32_t width</div><div class="ttdoc">The point cloud width (if organized as an image-structure).</div><div class="ttdef"><b>Definition:</b> point_cloud.h:413</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html_a4f34b45220c57f96607513ffad0d9582"><div class="ttname"><a href="classpcl_1_1_point_cloud.html#a4f34b45220c57f96607513ffad0d9582">pcl::PointCloud::height</a></div><div class="ttdeci">uint32_t height</div><div class="ttdoc">The point cloud height (if organized as an image-structure).</div><div class="ttdef"><b>Definition:</b> point_cloud.h:415</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html_a82e0be055a617e5e74102ed62712b352"><div class="ttname"><a href="classpcl_1_1_point_cloud.html#a82e0be055a617e5e74102ed62712b352">pcl::PointCloud::header</a></div><div class="ttdeci">pcl::PCLHeader header</div><div class="ttdoc">The point cloud header. It contains information about the acquisition time.</div><div class="ttdef"><b>Definition:</b> point_cloud.h:407</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html_af16a62638198313b9c093127c492c884"><div class="ttname"><a href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">pcl::PointCloud::points</a></div><div class="ttdeci">std::vector&lt; PointT, Eigen::aligned_allocator&lt; PointT &gt; &gt; points</div><div class="ttdoc">The point data.</div><div class="ttdef"><b>Definition:</b> point_cloud.h:410</div></div>
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